For many years, dark field scanning methodologies have been used to scan surfaces. Dark field scanning makes use of light scattered by the surface features to characterize and examine features of the surface. Such darkfield scanning can be used to detect defects in an inspected surface. In particular, semiconductor wafer surfaces and associated masks are subject to such scanning and inspection. In common usage, defects are frequently detected as aberrant light scattering features.
As is known to those having ordinary skill in the art, defects are fairly uncommon in the inspected surfaces. However, the consequences of such defects can be quite serious. The fact that defects occur in only one of many die patterns on a wafer or mask can be advantageously exploited by process engineers to detect defects. Consequently, defect detection is aided by systems that can compare the scattering patterns from multiple dies on a wafer and identify features which occur only in an isolated die. Such methodologies are commonly called die-to-die comparisons. Such defects can include, but are not limited to, pits, bumps, scratches, particles, process irregularities, and a number of other features which mar the surface. The presence of such defects on an inspection surface frequently cause a variation from the ordinary expected scattering pattern.
In dark field inspection a surface is illuminated by a light source and a single discrete light detector (placed so that it is not in the path of the reflected beam) is used to detect the light scattered by the surface. Thus, the background (the field) is dark. The scattered light received by the detector provides a representation of the surface where surface defects show up as lighter regions against the dark background or field. Hence, the name dark field scanning.
One of the problems in such dark field scanning is that for some surfaces the ordinary scattering pattern includes substantial regions of very bright signal. This bright signal can make the process of defect detection much more difficult as defects also produce bright signals. Thus, it is important to be able to differentiate defect caused signal from the ordinary scattering pattern.
In a conventional dark field surface inspection device an incident light beam is directed onto an inspection surface to generate a scattering pattern. The scattered light is collected by a lens or reflector and focused onto one or more discrete photodetector elements (for example PMT (photomultiplier tubes)). Alternative technologies direct the light onto a photodetector arranged in a spatial plane. By integrating light information from the photodetector elements, the presence of a defect can be determined.
A problem with such prior art systems is that they have difficulty discerning defect scatter from ordinary scatter generated by a patterned surface. Frequently, when patterned surfaces (e.g., the patterned surfaces of semiconductor wafers) are scanned, the resulting scattering pattern is detected as a “defect” by the discrete photodetector element. Even in systems which employ die-to-die comparison, small variations in the surface pattern and the resulting variation in scattering can mislead the system into falsely identifying a defect. Thus, portions of the (otherwise defect-free) patterned surface give false readings, as if they had defects in the surface. Conventional devices have attempted to circumvent this problem by so-called Fourier filtering. Under plane wave illumination, the intensity distribution at the back focal plane of a lens is proportional to the Fourier transform of the object. Further, for a repeating surface pattern (such as, for example a semiconductor memory array), the Fourier transform consists of a pattern of light and dark areas which remain constant as the wafer is scanned. By placing a filter in the back focal plane of the lens, the brightest portions of the signal can be blocked (filtered). In other words, filter having a selected pattern of opaque regions can be used to selectively and physically block the brightest portions of the optical signal generated by the repeating surface pattern. Thus, artifacts of repeating surface pattern can be filtered out and leave only non-repeating signals from particles and other defects. Such Fourier filtering is a common technology employed in wafer inspection machines from many manufacturers.
One of the limitations of Fourier filtering based instruments is that they can only inspect areas with repeating patterns (for example, arrays of memory cells) or blank areas. Critically, Fourier filtering of the type previously described is not useful for inspecting non-uniform surfaces like random logic areas. This poses a significant fundamental limitation on the technology.
For example, in a prior art machine such as the Hitachi Model IS-2300 inspection machine, darkfield Fourier filtering is combined with die-to-die image subtraction to effectuate wafer inspection. Using this technique, non-repeating pattern areas on a wafer can be inspected by the die-to-die comparison. However, even with such die-to-die comparison, conventional technologies still need Fourier filtering to obtain good sensitivity in the repeating array areas. For example, in dense memory cell areas of a wafer, a darkfield signal from the circuit pattern is usually so much stronger than that from the circuit lines in the peripheral areas that the dynamic range of the sensors are exceeded. As a result, either small particles in the array areas cannot be seen due to saturation, or small particles in the peripheral areas cannot be detected due to insufficient signal strength. Fourier filtering equalizes the darkfield signal so that small particles can be detected in dense or sparse areas at the same time.
Although prior art techniques are relatively capable of detecting particle type defects, their sensitivity to pattern defects is very poor. Additionally, since filtered images are usually dark without circuit features, it is not possible to do an accurate die-to-die image alignment, which is necessary for achieving good cancellation in a subtraction algorithm. One solution is to use an expensive mechanical stage of very high precision, but even with such a stage, due to the pattern placement variations on the wafer and residual errors of the stage, the achievable sensitivity is limited roughly to particles that are 0.5 μm and larger. This limit comes from the alignment errors in die-to-die image subtraction. Additionally, the filtering makes it difficult to detect defects in certain regions of the surface. Moreover, as surface patterns become more complicated (as is the case in modern VLSI circuit structures), the patterns become more complex, and more filtering must be implemented. As a result, less and less of the surface can be effectively scanned for defects. Additionally, although Fourier filtering can be extremely effective in filtering light scattered by regularly repeating array areas (e.g., memory cells), there is currently no similar technique that can be applied to areas of the wafer where the surface pattern is not regular and repeating. Examples of such areas include random logic areas. Unlike memory areas (which feature repeating surface patterns), areas without repeating surface patterns are far more difficult to filter. This is because the scattering pattern at the Fourier transform plane of a lens is not constant as the wafer is scanned. As a result, it is no longer practical to insert a fixed filter to selectively block light scattering caused by the surface pattern. Heretofore, there has not been a tool or methodology of providing fourier filtering of data obtained in dense logic areas or other surface areas having non-repeating surface patterns.
What is needed are dark field inspection tools and methodologies that can achieve filtering of the scattering signal in the presence of non-repeating surface patterns. Adaptively filtering the signal to accommodate surface features such as dense logic areas would be highly advantageous.